IBRAP Integrated Sample Figures
library(IBRAP)
library(ggpubr)
integrated <- readRDS('integration_analyses.rds')
datasets <- names(integrated)
norm.methods <- c('RAW', 'SCT', 'SCRAN', 'SCANPY')
clust.methods <- names(integrated$pancreas@methods$SCT@benchmark_results$clustering)
count <- 1
all_results <- data.frame(sample = character(), normalisation = character(), preprocessing = character(),
parameter = character(), ARI = numeric(), NMI = numeric(), ASW = numeric())
for(x in datasets) {
print(x)
for(t in 2:4) {
for(u in seq_along(clust.methods)) {
row.nam <- rownames(integrated[[x]]@methods[[t]]@benchmark_results[['clustering']][[clust.methods[[u]]]])
counter <- 1
for(m in rownames(integrated[[x]]@methods[[t]]@benchmark_results[['clustering']][[clust.methods[[u]]]])) {
all_results[count, 'sample'] <- x
all_results[count, 'normalisation'] <- norm.methods[t]
all_results[count, 'preprocessing'] <- clust.methods[u]
all_results[count, 'parameter'] <- row.nam[counter]
# print(clust.methods[u])
if(is.na(integrated[[x]]@methods[[t]]@benchmark_results[['clustering']][[clust.methods[[u]]]][m,4])) {
print('bump')
}
all_results[count, 'ARI'] <- integrated[[x]]@methods[[t]]@benchmark_results[['clustering']][[clust.methods[[u]]]][m,4]
all_results[count, 'NMI'] <- integrated[[x]]@methods[[t]]@benchmark_results[['clustering']][[clust.methods[[u]]]][m,5]
all_results[count, 'ASW'] <- integrated[[x]]@methods[[t]]@benchmark_results[['clustering']][[clust.methods[[u]]]][m,1]
count <- count + 1
counter <- counter + 1
}
}
}
}
all_results <- all_results[order(all_results$sample),]
list.of.results <- list()
for(i in datasets) {
list.of.results[[i]] <- all_results[all_results$sample==i,]
}
for(i in datasets) {
list.of.results[[i]]$ARI_rank <- rank(list.of.results[[i]]$ARI)
list.of.results[[i]]$NMI_rank <- rank(list.of.results[[i]]$NMI)
list.of.results[[i]]$ASW_rank <- rank(list.of.results[[i]]$ASW)
}
for(i in datasets) {
list.of.results[[i]]$Score <- apply(X = list.of.results[[i]][,c('ARI_rank','NMI_rank','ASW_rank')], MARGIN = 1, FUN = function(x) {
mean(x)
})
}
all_results <- do.call(rbind, list.of.results)
tempo <- strsplit(x = all_results[grepl(pattern = 'neighbourhood', all_results$parameter),]$parameter, split = '_')
tempor <- list()
count <- 1
for(u in tempo) {
tempor[[count]] <- tempo[[count]][3]
count <- count + 1
}
all_results[grepl(pattern = 'neighbourhood', all_results$parameter),]$parameter <- unlist(tempor)
all_results$Score_scaled <- 100
for(x in unique(all_results$sample)) {
all_results[all_results$sample==x,]$Score_scaled <- scales::rescale(x = all_results[all_results$sample==x,]$Score, to = c(0,100))
}
all_results$Score_percent <- all_results$Score/1172*100
all_results$integration = ''
all_results$integration[grepl(pattern = 'HARMONY', x = all_results$preprocessing)] = 'HARMONY'
all_results$integration[grepl(pattern = 'SCANORAMA', x = all_results$preprocessing)] = 'SCANORAMA'
all_results$integration[grepl(pattern = 'CCA', x = all_results$preprocessing)] = 'SEURAT CCA'
all_results$integration[grepl(pattern = 'BBKNN', x = all_results$preprocessing)] = 'BBKNN'
all_results$integration[all_results$integration==''] = 'UNCORRECTED'
all_results$preprocessing <- gsub(x = all_results$preprocessing, pattern = '_BENCHMARKED', replacement = '')write.csv(x = all_results, file = 'supplementary_table_5.csv')Creating Figure 4
Panel A
plot1 <- ggplot(data = all_results[all_results=='pancreas',],
mapping = aes(y = ARI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ARI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot2 <- ggplot(data = all_results[all_results=='pancreas',],
mapping = aes(y = NMI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('Analysis 1') +
ylab('NMI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot3 <- ggplot(data = all_results[all_results=='pancreas',],
mapping = aes(y = ASW, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ASW') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
ggpubr::ggarrange(plot1,plot2,plot3,nrow = 1, ncol = 3, common.legend = T)
Panel B
plot4 <- ggplot(data = all_results[all_results=='equal',],
mapping = aes(y = ARI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ARI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot5 <- ggplot(data = all_results[all_results=='equal',],
mapping = aes(y = NMI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('Analysis 2') +
ylab('NMI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot6 <- ggplot(data = all_results[all_results=='equal',],
mapping = aes(y = ASW, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ASW') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
ggpubr::ggarrange(plot4,plot5,plot6,nrow = 1, ncol = 3, common.legend = T)
Panel C
plot7 <- ggplot(data = all_results[all_results=='unequal',],
mapping = aes(y = ARI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ARI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot8 <- ggplot(data = all_results[all_results=='unequal',],
mapping = aes(y = NMI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('Analysis 3') +
ylab('NMI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot9 <- ggplot(data = all_results[all_results=='unequal',],
mapping = aes(y = ASW, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ASW') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
ggpubr::ggarrange(plot7,plot8,plot9,nrow = 1, ncol = 3, common.legend = T)
Panel D
plot10 <- ggplot(data = all_results[all_results=='symsim_simulations_1',],
mapping = aes(y = ARI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ARI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot11 <- ggplot(data = all_results[all_results=='symsim_simulations_1',],
mapping = aes(y = NMI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('Analysis 4') +
ylab('NMI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot12 <- ggplot(data = all_results[all_results=='symsim_simulations_1',],
mapping = aes(y = ASW, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ASW') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
ggpubr::ggarrange(plot10,plot11,plot12,nrow = 1, ncol = 3, common.legend = T)
Supplementary Figure 4
plot13 <- ggplot(data = all_results[all_results=='symsim_simulations_2',],
mapping = aes(y = ARI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ARI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot14 <- ggplot(data = all_results[all_results=='symsim_simulations_2',],
mapping = aes(y = NMI, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('Analysis 5') +
ylab('NMI') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot15 <- ggplot(data = all_results[all_results=='symsim_simulations_2',],
mapping = aes(y = ASW, x = integration, fill = normalisation)) +
geom_boxplot(na.rm = TRUE) +
theme_classic() +
ggtitle('') +
ylab('ASW') + xlab('') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
ggpubr::ggarrange(plot13,plot14,plot15,nrow = 1, ncol = 3, common.legend = T)
Supplementary Figure 5
Panel A
plot.integration.benchmarking(object = integrated$pancreas, c('SCT','SCRAN','SCANPY')) +
ggtitle('Analysis 1') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot.integration.benchmarking(object = integrated$equal, c('SCT','SCRAN','SCANPY')) +
ggtitle('Analysis 2') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot.integration.benchmarking(object = integrated$unequal, c('SCT','SCRAN','SCANPY')) +
ggtitle('Analysis 3') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot.integration.benchmarking(object = integrated$symsim_simulations_1, c('SCT','SCRAN','SCANPY')) +
ggtitle('Analysis 4') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
plot.integration.benchmarking(object = integrated$symsim_simulations_2, c('SCT','SCRAN','SCANPY')) +
ggtitle('Analysis 5') +
theme(axis.text.x = element_text(colour = 'black', angle = 90, hjust = 1,
face = 'bold', size = 12),
plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.text.y = element_text(colour = 'black', face = 'bold', size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 20),
legend.text = element_text(face = 'bold', color = 'black', size = 12),
axis.title.x.bottom = element_text(face = 'bold', size = 15),
axis.title.y.left = element_text(face = 'bold', size = 15)) +
guides(fill=guide_legend(title="Normalisation Method"))
Supplementary Figure 4 B
SCT_uncorrected <- mean(integrated$pancreas@methods$SCT@benchmark_results$integration$SCT_uncorrected,
integrated$equal@methods$SCT@benchmark_results$integration$SCT_uncorrected,
integrated$unequal@methods$SCT@benchmark_results$integration$SCT_uncorrected,
integrated$symsim_simulations_1@methods$SCT@benchmark_results$integration$SCT_uncorrected,
integrated$symsim_simulations_2@methods$SCT@benchmark_results$integration$SCT_uncorrected)
SCT_harmony <- mean(integrated$pancreas@methods$SCT@benchmark_results$integration$SCT_harmony,
integrated$equal@methods$SCT@benchmark_results$integration$SCT_harmony,
integrated$unequal@methods$SCT@benchmark_results$integration$SCT_harmony,
integrated$symsim_simulations_1@methods$SCT@benchmark_results$integration$SCT_harmony,
integrated$symsim_simulations_2@methods$SCT@benchmark_results$integration$SCT_harmony)
SCT_scanorama <- mean(integrated$pancreas@methods$SCT@benchmark_results$integration$SCT_scanorama,
integrated$equal@methods$SCT@benchmark_results$integration$SCT_scanorama,
integrated$unequal@methods$SCT@benchmark_results$integration$SCT_scanorama,
integrated$symsim_simulations_1@methods$SCT@benchmark_results$integration$SCT_scanorama,
integrated$symsim_simulations_2@methods$SCT@benchmark_results$integration$SCT_scanorama)
SCT_bbknn <- mean(integrated$pancreas@methods$SCT@benchmark_results$integration$SCT_bbknn,
integrated$equal@methods$SCT@benchmark_results$integration$SCT_bbknn,
integrated$unequal@methods$SCT@benchmark_results$integration$SCT_bbknn,
integrated$symsim_simulations_1@methods$SCT@benchmark_results$integration$SCT_bbknn,
integrated$symsim_simulations_2@methods$SCT@benchmark_results$integration$SCT_bbknn)
SCT_cca <- mean(integrated$pancreas@methods$SCT@benchmark_results$integration$SCT_seurat,
integrated$equal@methods$SCT@benchmark_results$integration$SCT_seurat,
integrated$unequal@methods$SCT@benchmark_results$integration$SCT_seurat,
integrated$symsim_simulations_1@methods$SCT@benchmark_results$integration$SCT_cca,
integrated$symsim_simulations_2@methods$SCT@benchmark_results$integration$SCT_cca)
SCRAN_uncorrected <- mean(integrated$pancreas@methods$SCRAN@benchmark_results$integration$SCRAN_uncorrected,
integrated$equal@methods$SCRAN@benchmark_results$integration$SCRAN_uncorrected,
integrated$unequal@methods$SCRAN@benchmark_results$integration$SCRAN_uncorrected,
integrated$symsim_simulations_1@methods$SCRAN@benchmark_results$integration$SCRAN_uncorrected,
integrated$symsim_simulations_2@methods$SCRAN@benchmark_results$integration$SCRAN_uncorrected)
SCRAN_harmony <- mean(integrated$pancreas@methods$SCRAN@benchmark_results$integration$SCRAN_harmony,
integrated$equal@methods$SCRAN@benchmark_results$integration$SCRAN_harmony,
integrated$unequal@methods$SCRAN@benchmark_results$integration$SCRAN_harmony,
integrated$symsim_simulations_1@methods$SCRAN@benchmark_results$integration$SCRAN_harmony,
integrated$symsim_simulations_2@methods$SCRAN@benchmark_results$integration$SCRAN_harmony)
SCRAN_scanorama <- mean(integrated$pancreas@methods$SCRAN@benchmark_results$integration$SCRAN_scanorama,
integrated$equal@methods$SCRAN@benchmark_results$integration$SCRAN_scanorama,
integrated$unequal@methods$SCRAN@benchmark_results$integration$SCRAN_scanorama,
integrated$symsim_simulations_1@methods$SCRAN@benchmark_results$integration$SCRAN_scanorama,
integrated$symsim_simulations_2@methods$SCRAN@benchmark_results$integration$SCRAN_scanorama)
SCRAN_bbknn <- mean(integrated$pancreas@methods$SCRAN@benchmark_results$integration$SCRAN_bbknn,
integrated$equal@methods$SCRAN@benchmark_results$integration$SCRAN_bbknn,
integrated$unequal@methods$SCRAN@benchmark_results$integration$SCRAN_bbknn,
integrated$symsim_simulations_1@methods$SCRAN@benchmark_results$integration$SCRAN_bbknn,
integrated$symsim_simulations_2@methods$SCRAN@benchmark_results$integration$SCRAN_bbknn)
SCRAN_cca <- mean(integrated$pancreas@methods$SCRAN@benchmark_results$integration$SCRAN_seurat,
integrated$equal@methods$SCRAN@benchmark_results$integration$SCRAN_seurat,
integrated$unequal@methods$SCRAN@benchmark_results$integration$SCRAN_seurat,
integrated$symsim_simulations_1@methods$SCRAN@benchmark_results$integration$SCRAN_cca,
integrated$symsim_simulations_2@methods$SCRAN@benchmark_results$integration$SCRAN_cca)
SCANPY_uncorrected <- mean(integrated$pancreas@methods$SCANPY@benchmark_results$integration$SCANPY_uncorrected,
integrated$equal@methods$SCANPY@benchmark_results$integration$SCANPY_uncorrected,
integrated$unequal@methods$SCANPY@benchmark_results$integration$SCANPY_uncorrected,
integrated$symsim_simulations_1@methods$SCANPY@benchmark_results$integration$SCANPY_uncorrected,
integrated$symsim_simulations_2@methods$SCANPY@benchmark_results$integration$SCANPY_uncorrected)
SCANPY_harmony <- mean(integrated$pancreas@methods$SCANPY@benchmark_results$integration$SCANPY_harmony,
integrated$equal@methods$SCANPY@benchmark_results$integration$SCANPY_harmony,
integrated$unequal@methods$SCANPY@benchmark_results$integration$SCANPY_harmony,
integrated$symsim_simulations_1@methods$SCANPY@benchmark_results$integration$SCANPY_harmony,
integrated$symsim_simulations_2@methods$SCANPY@benchmark_results$integration$SCANPY_harmony)
SCANPY_scanorama <- mean(integrated$pancreas@methods$SCANPY@benchmark_results$integration$SCANPY_scanorama,
integrated$equal@methods$SCANPY@benchmark_results$integration$SCANPY_scanorama,
integrated$unequal@methods$SCANPY@benchmark_results$integration$SCANPY_scanorama,
integrated$symsim_simulations_1@methods$SCANPY@benchmark_results$integration$SCANPY_scanorama,
integrated$symsim_simulations_2@methods$SCANPY@benchmark_results$integration$SCANPY_scanorama)
SCANPY_bbknn <- mean(integrated$pancreas@methods$SCANPY@benchmark_results$integration$SCANPY_bbknn,
integrated$equal@methods$SCANPY@benchmark_results$integration$SCANPY_bbknn,
integrated$unequal@methods$SCANPY@benchmark_results$integration$SCANPY_bbknn,
integrated$symsim_simulations_1@methods$SCANPY@benchmark_results$integration$SCANPY_bbknn,
integrated$symsim_simulations_2@methods$SCANPY@benchmark_results$integration$SCANPY_bbknn)
SCANPY_cca <- mean(integrated$pancreas@methods$SCANPY@benchmark_results$integration$SCANPY_seurat,
integrated$equal@methods$SCANPY@benchmark_results$integration$SCANPY_seurat,
integrated$unequal@methods$SCANPY@benchmark_results$integration$SCANPY_seurat,
integrated$symsim_simulations_1@methods$SCANPY@benchmark_results$integration$SCANPY_cca,
integrated$symsim_simulations_2@methods$SCANPY@benchmark_results$integration$SCANPY_cca)
df <- data.frame(UNCORRECTED = c(SCT_uncorrected, SCRAN_uncorrected, SCANPY_uncorrected),
HARMONY = c(SCT_harmony, SCRAN_harmony, SCANPY_harmony),
SCANORAMA = c(SCT_scanorama, SCRAN_scanorama, SCANPY_scanorama),
CCA = c(SCT_cca, SCRAN_cca, SCANPY_cca),
BBKNN = c(SCT_bbknn, SCRAN_bbknn, SCANPY_bbknn))
rownames(df) <- c('SCT','SCRAN','SCANPY')
library(pheatmap)
pheatmap(mat = df, display_numbers = T)
Supplementary Figure 6
library(ggpubr)
plot_1 <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'PCA_BBKNN_BBKNN:LOUVAIN', column = 'neighbourhood_graph_res.0.2') +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_2 <- plot.reduced.dim(object = integrated$pancreas, reduction = 'SEURAT_UMAP', assay = 'SCANPY',
clust.method = 'CCA_NN:LOUVAIN', column = 'neighbourhood_graph_res.0.2') +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_3 <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'celltype', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
plot_4 <- plot.reduced.dim(object = integrated$pancreas, reduction = 'SEURAT_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'celltype', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
ggarrange(plot_1, plot_2, plot_3, plot_4, nrow = 2, ncol = 2)
Supplementary Figure 7
plot_1 <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_HARMONY_UMAP', assay = 'SCANPY',
clust.method = 'PCA_HARMONY_UMAP:PAM', column = 'k_6') +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_2 <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'PCA_BBKNN_BBKNN:LEIDEN', column = 'neighbourhood_graph_res.0.1') +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_3 <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_HARMONY_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'celltype', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
plot_4 <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'celltype', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
ggarrange(plot_1, plot_2, plot_3, plot_4, nrow = 2, ncol = 2)
Supplementary Figure 8
plot_1 <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCT',
clust.method = 'PCA_BBKNN_BBKNN:LOUVAIN', column = 'neighbourhood_graph_res.0.2') +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_2 <- plot.reduced.dim(object = integrated$unequal, reduction = 'SEURAT_UMAP', assay = 'SCANPY',
clust.method = 'CCA_NN:LOUVAIN', column = 'neighbourhood_graph_res.0.2') +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_3 <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'celltype', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
plot_4 <- plot.reduced.dim(object = integrated$unequal, reduction = 'SEURAT_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'celltype', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
ggarrange(plot_1, plot_2, plot_3, plot_4, nrow = 2, ncol = 2)
Supplementary Figure 9
plot_1 <-plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'CCA_UMAP', assay = 'SCANPY',
clust.method = 'CCA_UMAP:PAM', column = 'k_3') +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_2 <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'SCANORAMA_UMAP', assay = 'SCANPY',
clust.method = 'SCANORAMA_NN:LOUVAIN', column = 'res_0.1') +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_3 <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'CCA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'CellType', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
plot_4 <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'SCANORAMA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'CellType', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
ggarrange(plot_1, plot_2, plot_3, plot_4, nrow = 2, ncol = 2)
Supplementary Figure 10
plot_1 <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'CCA_UMAP', assay = 'SCANPY',
clust.method = 'CCA_UMAP:PAM', column = 'k_3', add.label = T, label.size = 10) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_2 <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'SCANORAMA_UMAP', assay = 'SCANPY',
clust.method = 'SCANORAMA_NN:LOUVAIN', column = 'res_0.1', add.label = T, label.size = 10) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12))
plot_3 <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'CCA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'CellType', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
plot_4 <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'SCANORAMA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'CellType', add.label = F) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 12),
legend.title = element_text(face = 'bold', color = 'black', size = 12),
legend.text = element_text(face = 'bold', color = 'black', size = 12))
ggarrange(plot_1, plot_2, plot_3, plot_4, nrow = 2, ncol = 2)
Supplementary 11
SCT_uncorrected <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('SCTransform') + ylab('Uncorrected') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_harmony <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_HARMONY_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Harmony') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_scanorama <- plot.reduced.dim(object = integrated$pancreas, reduction = 'SCANORAMA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Scanorama') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_bbknn <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('BBKNN') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_cca <- plot.reduced.dim(object = integrated$pancreas, reduction = 'SEURAT_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('CCA') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_uncorrected <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scran') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_harmony <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_HARMONY_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_scanorama <- plot.reduced.dim(object = integrated$pancreas, reduction = 'SCANORAMA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_bbknn <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_cca <- plot.reduced.dim(object = integrated$pancreas, reduction = 'SEURAT_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_uncorrected <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scanpy') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCANPY_harmony <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_HARMONY_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_scanorama <- plot.reduced.dim(object = integrated$pancreas, reduction = 'SCANORAMA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_bbknn <- plot.reduced.dim(object = integrated$pancreas, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_cca <- plot.reduced.dim(object = integrated$pancreas, reduction = 'SEURAT_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'dataset', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
ggarrange(SCT_uncorrected, SCRAN_uncorrected, SCANPY_uncorrected,
SCT_harmony, SCRAN_harmony, SCANPY_harmony,
SCT_scanorama, SCRAN_scanorama, SCANPY_scanorama,
SCT_bbknn, SCRAN_bbknn, SCANPY_bbknn,
SCT_cca, SCRAN_cca, SCANPY_cca, ncol = 3, nrow = 5)
Supplementary Figure 12
SCT_uncorrected <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('SCTransform') + ylab('Uncorrected') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_harmony <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_HARMONY_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Harmony') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_scanorama <- plot.reduced.dim(object = integrated$equal, reduction = 'SCANORAMA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Scanorama') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_bbknn <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('BBKNN') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_cca <- plot.reduced.dim(object = integrated$equal, reduction = 'SEURAT_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('CCA') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_uncorrected <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scran') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_harmony <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_HARMONY_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_scanorama <- plot.reduced.dim(object = integrated$equal, reduction = 'SCANORAMA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_bbknn <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_cca <- plot.reduced.dim(object = integrated$equal, reduction = 'SEURAT_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_uncorrected <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scanpy') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCANPY_harmony <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_HARMONY_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_scanorama <- plot.reduced.dim(object = integrated$equal, reduction = 'SCANORAMA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_bbknn <- plot.reduced.dim(object = integrated$equal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_cca <- plot.reduced.dim(object = integrated$equal, reduction = 'SEURAT_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
ggarrange(SCT_uncorrected, SCRAN_uncorrected, SCANPY_uncorrected,
SCT_harmony, SCRAN_harmony, SCANPY_harmony,
SCT_scanorama, SCRAN_scanorama, SCANPY_scanorama,
SCT_bbknn, SCRAN_bbknn, SCANPY_bbknn,
SCT_cca, SCRAN_cca, SCANPY_cca, ncol = 3, nrow = 5)
Supplementary Figure 13
SCT_uncorrected <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('SCTransform') + ylab('Uncorrected') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_harmony <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_HARMONY_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Harmony') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_scanorama <- plot.reduced.dim(object = integrated$unequal, reduction = 'SCANORAMA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Scanorama') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_bbknn <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('BBKNN') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_cca <- plot.reduced.dim(object = integrated$unequal, reduction = 'SEURAT_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('CCA') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_uncorrected <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scran') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_harmony <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_HARMONY_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_scanorama <- plot.reduced.dim(object = integrated$unequal, reduction = 'SCANORAMA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_bbknn <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_cca <- plot.reduced.dim(object = integrated$unequal, reduction = 'SEURAT_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_uncorrected <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scanpy') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCANPY_harmony <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_HARMONY_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_scanorama <- plot.reduced.dim(object = integrated$unequal, reduction = 'SCANORAMA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_bbknn <- plot.reduced.dim(object = integrated$unequal, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_cca <- plot.reduced.dim(object = integrated$unequal, reduction = 'SEURAT_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'original.project', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
ggarrange(SCT_uncorrected, SCRAN_uncorrected, SCANPY_uncorrected,
SCT_harmony, SCRAN_harmony, SCANPY_harmony,
SCT_scanorama, SCRAN_scanorama, SCANPY_scanorama,
SCT_bbknn, SCRAN_bbknn, SCANPY_bbknn,
SCT_cca, SCRAN_cca, SCANPY_cca, ncol = 3, nrow = 5)
Supplementary Figure 14
SCT_uncorrected <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'PCA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('SCTransform') + ylab('Uncorrected') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_harmony <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'PCA_HARMONY_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Harmony') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_scanorama <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'SCANORAMA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Scanorama') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_bbknn <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('BBKNN') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_cca <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'CCA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('CCA') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_uncorrected <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'PCA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scran') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_harmony <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'PCA_HARMONY_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_scanorama <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'SCANORAMA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_bbknn <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_cca <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'CCA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_uncorrected <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'PCA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scanpy') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCANPY_harmony <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'PCA_HARMONY_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_scanorama <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'SCANORAMA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_bbknn <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_cca <- plot.reduced.dim(object = integrated$symsim_simulations_1, reduction = 'CCA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
ggarrange(SCT_uncorrected, SCRAN_uncorrected, SCANPY_uncorrected,
SCT_harmony, SCRAN_harmony, SCANPY_harmony,
SCT_scanorama, SCRAN_scanorama, SCANPY_scanorama,
SCT_bbknn, SCRAN_bbknn, SCANPY_bbknn,
SCT_cca, SCRAN_cca, SCANPY_cca, ncol = 3, nrow = 5)
Supplementary Figure 15
SCT_uncorrected <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'PCA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('SCTransform') + ylab('Uncorrected') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25),
axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_harmony <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'PCA_HARMONY_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Harmony') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_scanorama <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'SCANORAMA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('Scanorama') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_bbknn <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('BBKNN') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCT_cca <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'CCA_UMAP', assay = 'SCT',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ylab('CCA') +
theme(axis.title.y.left = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_uncorrected <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'PCA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scran') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCRAN_harmony <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'PCA_HARMONY_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_scanorama <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'SCANORAMA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_bbknn <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCRAN_cca <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'CCA_UMAP', assay = 'SCRAN',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_uncorrected <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'PCA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5)) +
ggtitle('Scanpy') +
theme(plot.title = element_text(hjust = 0.5, face = 'bold', size = 25), legend.position="none")
SCANPY_harmony <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'PCA_HARMONY_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_scanorama <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'SCANORAMA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_bbknn <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'PCA_BBKNN_BBKNN:UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
SCANPY_cca <- plot.reduced.dim(object = integrated$symsim_simulations_2, reduction = 'CCA_UMAP', assay = 'SCANPY',
clust.method = 'metadata', column = 'batch', add.label = F, label.size = 5) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.line = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank(),
plot.title = element_text(face = 'bold', hjust = 0.5, size = 12),
plot.subtitle = element_text(face = 'bold', hjust = 0.5, size = 5), legend.position="none")
ggarrange(SCT_uncorrected, SCRAN_uncorrected, SCANPY_uncorrected,
SCT_harmony, SCRAN_harmony, SCANPY_harmony,
SCT_scanorama, SCRAN_scanorama, SCANPY_scanorama,
SCT_bbknn, SCRAN_bbknn, SCANPY_bbknn,
SCT_cca, SCRAN_cca, SCANPY_cca, ncol = 3, nrow = 5)